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Article

Decoding Plant-Based Beverages: An Integrated Study Combining ATR-FTIR Spectroscopy and Microscopic Image Analysis with Chemometrics

by
Paris Christodoulou
1,
Stratoniki Athanasopoulou
1,
Georgia Ladika
1,
Spyros J. Konteles
1,
Dionisis Cavouras
2,
Vassilia J. Sinanoglou
1,* and
Eftichia Kritsi
1,*
1
Laboratory of Chemistry, Analysis & Design of Food Processes, Department of Food Science and Technology, University of West Attica, Agiou Spyridonos, 12243 Egaleo, Greece
2
Department of Biomedical Engineering, University of West Attica, Agiou Spyridonos, 12243 Egaleo, Greece
*
Authors to whom correspondence should be addressed.
AppliedChem 2025, 5(3), 16; https://doi.org/10.3390/appliedchem5030016
Submission received: 10 June 2025 / Revised: 8 July 2025 / Accepted: 10 July 2025 / Published: 16 July 2025

Abstract

As demand for plant-based beverages grows, analytical tools are needed to classify and understand their structural and compositional diversity. This study applied a multi-analytical approach to characterize 41 commercial almond-, oat-, rice- and soy-based beverages, evaluating attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, protein secondary structure proportions, colorimetry, and microscopic image texture analysis. A total of 26 variables, derived from ATR-FTIR and protein secondary structure assessment, were employed in multivariate models, using partial least squares discriminant analysis (PLS-DA) and orthogonal PLS-DA (OPLS-DA) to evaluate classification performance. The results indicated clear group separation, with soy and rice beverages forming distinct clusters while almond and oat samples showing partial overlap. Variable importance in projection (VIP) scores revealed that β-turn and α-helix protein structures, along with carbohydrate-associated spectral bands, were the key features for beverages’ classification. Textural features derived from microscopy images correlated with sugar and carbohydrate content and color parameters were also employed to describe beverages’ differences related to sugar content and visual appearance in terms of homogeneity. These findings demonstrate that combining ATR-FTIR spectral data with protein secondary structure data enables the effective classification of plant-based beverages, while microscopic image textural and color parameters offer additional extended product characterization.
Keywords: plant-based beverages; attenuated total reflectance Fourier transform infrared spectroscopy; color; microscopic image analysis; protein secondary structure; principal component analysis; soy; almond; rice; oat plant-based beverages; attenuated total reflectance Fourier transform infrared spectroscopy; color; microscopic image analysis; protein secondary structure; principal component analysis; soy; almond; rice; oat

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MDPI and ACS Style

Christodoulou, P.; Athanasopoulou, S.; Ladika, G.; Konteles, S.J.; Cavouras, D.; Sinanoglou, V.J.; Kritsi, E. Decoding Plant-Based Beverages: An Integrated Study Combining ATR-FTIR Spectroscopy and Microscopic Image Analysis with Chemometrics. AppliedChem 2025, 5, 16. https://doi.org/10.3390/appliedchem5030016

AMA Style

Christodoulou P, Athanasopoulou S, Ladika G, Konteles SJ, Cavouras D, Sinanoglou VJ, Kritsi E. Decoding Plant-Based Beverages: An Integrated Study Combining ATR-FTIR Spectroscopy and Microscopic Image Analysis with Chemometrics. AppliedChem. 2025; 5(3):16. https://doi.org/10.3390/appliedchem5030016

Chicago/Turabian Style

Christodoulou, Paris, Stratoniki Athanasopoulou, Georgia Ladika, Spyros J. Konteles, Dionisis Cavouras, Vassilia J. Sinanoglou, and Eftichia Kritsi. 2025. "Decoding Plant-Based Beverages: An Integrated Study Combining ATR-FTIR Spectroscopy and Microscopic Image Analysis with Chemometrics" AppliedChem 5, no. 3: 16. https://doi.org/10.3390/appliedchem5030016

APA Style

Christodoulou, P., Athanasopoulou, S., Ladika, G., Konteles, S. J., Cavouras, D., Sinanoglou, V. J., & Kritsi, E. (2025). Decoding Plant-Based Beverages: An Integrated Study Combining ATR-FTIR Spectroscopy and Microscopic Image Analysis with Chemometrics. AppliedChem, 5(3), 16. https://doi.org/10.3390/appliedchem5030016

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